Pratyush is an 18-year-old graduate student at Stanford University pursuing an M.S. in Computer Science with a specialization in AI supported by the NSF GRFP Fellowship. He began his undergraduate education at age 14 through the CSULA Early Entrance Program and transferred to UC Irvine where he graduated with a B.S. in Computer Science and minor in Statistics at the age of 18. Throughout his undergraduate education he was constantly involved in machine learning and computer science research and coursework. Pratyush received numerous scholarships for his academic excellence and research experiences, including from Edison International, Phyllis Allen Keys Endowment Fund, and Norman L. Eyster and Noemie E. Eyster Endowment Fund.
Pratyush’s work is focused on machine learning and artificial intelligence, and he has numerous research and internship experiences in these fields. He has presented his research at various international conferences including at the MAA/AMS Joint Mathematics Meeting 2020, the largest conference of mathematicians in the world, and ICDATA ’20, one of the largest data science conferences globally. He has researched and developed machine learning models for various institutions in multiple industries including at the Lawrence Berkeley National Laboratory, City of Los Angeles, NASA JPL through the DIRECT-STEM program, USC Viterbi ISI, and jointly with Amazon and LA County WDACS.
Currently, Pratyush is working on research involving applications of machine learning for spatiotemporal forecasting, robust adaptation, and realtime monitoring. At UC Irvine, Pratyush was named a 2021 Goldwater Scholar, a prestigious national scholarship awarded to students with excellent academic and research skills. He is also currently working as a student researcher at the Lawrence Berkeley National Laboratory Energy Sciences Network (ESNet). In 2022, he was awarded the NSF Graduate Research Fellowships Program (GRFP) Fellowship, which recognizes and supports outstanding graduate students in NSF-supported STEM disciplines.